Abstract—This paper reports the temporal structures of the relationships between 24-hour heart rate variability (HRV) and physical activity (PA) in clinical big data of simultaneously recorded electrocardiograms (ECG) and actigraphic data in 21,682 male and 29,446 female patients (age, 20-100 yr). We found that SDNN (standard deviation of 24-hour normal-to-normal R-R interval [NN interval] of ECG) and PA during daytime, evening, and nighttime decreased with age. In regression models adjusted for the effect of age, daytime PA explained 7% of inter-individual variance in SDNN, while evening and early morning PA explained only <0.6% and nighttime PA negatively contributed to SDNN. Daytime but not nighttime PA is positively associated with increased 24-hour HRV.

Index Terms—Actigraphic data, biomedical big data, electrocardiogram, heart rate variability, lifestyle modification, physical activity.

The authors are with Nagoya City University Graduate School of Medical Science, 1 Kawasumi, Mizuho-cho Mizuho-ku, Nagoya 467-8602, Japan (email: Hayano@med.nagoya-cu.ac.jp).

Cite: Junichiro Hayano, Yuki Furukawa, Emi Yuda, Yutaka Yoshida, "Association of 24-Hour Heart Rate Variability and Daytime Physical Activity: ALLSTAR Big Data Analysis," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 8, no. 1, pp. 61-67, 2018.